Book contents
- Frontmatter
- Contents
- List of exercises
- Preface to the series
- Preface
- 1 The subjective interpretation of probability
- 2 Bayesian inference
- 3 Point estimation
- 4 Frequentist properties of Bayesian estimators
- 5 Interval estimation
- 6 Hypothesis testing
- 7 Prediction
- 8 Choice of prior
- 9 Asymptotic Bayes
- 10 The linear regression model
- 11 Basics of Bayesian computation
- 12 Hierarchical models
- 13 The linear regression model with general covariance matrix
- 14 Latent variable models
- 15 Mixture models
- 16 Bayesian model averaging and selection
- 17 Some stationary time series models
- 18 Some nonstationary time series models
- Appendix
- Bibliography
- Index
12 - Hierarchical models
Published online by Cambridge University Press: 05 June 2012
Book contents
- Frontmatter
- Contents
- List of exercises
- Preface to the series
- Preface
- 1 The subjective interpretation of probability
- 2 Bayesian inference
- 3 Point estimation
- 4 Frequentist properties of Bayesian estimators
- 5 Interval estimation
- 6 Hypothesis testing
- 7 Prediction
- 8 Choice of prior
- 9 Asymptotic Bayes
- 10 The linear regression model
- 11 Basics of Bayesian computation
- 12 Hierarchical models
- 13 The linear regression model with general covariance matrix
- 14 Latent variable models
- 15 Mixture models
- 16 Bayesian model averaging and selection
- 17 Some stationary time series models
- 18 Some nonstationary time series models
- Appendix
- Bibliography
- Index
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- Bayesian Econometric Methods , pp. 169 - 190Publisher: Cambridge University PressPrint publication year: 2007